The proposed algorithm required two training steps. First, a text classifier learns to classify metaphorical from literal sentences.

Second, metaphorical sentences, which were correctly classified by our classifier as metaphorical, were passed to a reconstruction step, where metaphorical tokens were masked and then recovered through extraction (T5, BART) and masked language modeling (BERT, XLM-R).